Wyatt Nelson

An integrated genotyping approach for HLA and other complex genetic systems

Clinical immunogenetics laboratories performing routine sequencing of human leukocyte antigen (HLA) genes in support of hematopoietic cell transplantation are motivated to upgrade to next-generation sequencing (NGS) technology by its potential for cost savings as well as testing accuracy and flexibility. While NGS machines are available and simple to operate, there are few systems available that provide comprehensive sample preparation and data analysis workflows to complete the process. We report on the development and testing of the Integrated Genotyping System (IGS), which has been designed to specifically address the challenges associated with the adoption of NGS in clinical laboratories. To validate the system for a variety of sample DNA sources, we have tested 336 DNA specimens from whole blood, dried blood spots, buccal swabs, and lymphoblastoid cell lines. HLA class I and class II genotypes were derived from amplicon sequencing of HLA-A, -B, -C for exons 1-7 and HLA-DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4, -DRB5 for exons 1-4. Additionally, to demonstrate the extensibility of the IGS to other genetic loci, KIR haplotyping of 93 samples was carried out in parallel with HLA typing using a workflow based on the HLA system. These results are discussed with respect to their applications in the clinical setting and consequent potential for advancing precision medicine.

Next generation sequencing to determine HLA class II genotypes in a cohort of hematopoietic cell transplant patients and donors.

Current high-resolution HLA typing technologies frequently produce ambiguous results that mandate extended testing prior to reporting. Through multiplex sequencing of individual amplicons from many individuals at multiple loci, next generation sequencing (NGS) promises to eliminate heterozygote ambiguities and extend the breadth of genetic data acquired with little additional effort. We report here on assessment of a novel NGS HLA genotyping system for resequencing exons 2 and 3 of DRB1/B3/B4/B5, DQA1 and DQB1 and exon 2 of DPA1 and DPB1 on the MiSeq platform. In a cohort of 2605 hematopoietic cell transplant recipients and donors, NGS achieved 99.6% accuracy for DRB1 allele assignments and 99.5% for DQB1, compared to legacy genotypes generated pretransplant. NGS provided at least single 4-digit allele resolution for 97% of genotypes at DRB1 and 100% at DQB1. Overall, NGS typing identified 166 class II alleles, including 9 novel sequences with greater than 99% accuracy for DRB1 and DQB1 genotypes and elimination of diploid ambiguities through in-phase sequencing demonstrated the robust reliability of the NGS HLA genotyping reagents and analysis software employed in this study.

HLA class II genes modulate vaccine-induced antibody responses to affect HIV-1 acquisition

HLA class II modulated the quantity, quality, and efficacy of antibody responses in the RV144 HIV vaccine trial. An HIV vaccine on the Orient Express Unlike an Agatha Christie novel, biomedical mysteries are not always neatly solved at the end of a trial. The RV144 HIV vaccine trial is a prime example, and follow-up studies have searched for correlates of protection from HIV acquisition. Two different antibody responses have been associated with HIV acquisition—one protecting from acquisition and the other mitigating the protective response. Now, Prentice et al. demonstrate that these differences occur only in the presence of particular host HLA alleles. Thus, the genetic background of the recipients may determine whether individuals elicit a protective response to the HIV vaccine. In the RV144 vaccine trial, two antibody responses were found to correlate with HIV-1 acquisition. Because human leukocyte antigen (HLA) class II–restricted CD4+ T cells are involved in antibody production, we tested whether HLA class II genotypes affected HIV-1–specific antibody levels and HIV-1 acquisition in 760 individuals. Indeed, antibody responses correlated with acquisition only in the presence of single host HLA alleles. Envelope (Env)–specific immunoglobulin A (IgA) antibodies were associated with increased risk of acquisition specifically in individuals with DQB1*06. IgG antibody responses to Env amino acid positions 120 to 204 were higher and were associated with decreased risk of acquisition and increased vaccine efficacy only in the presence of DPB1*13. Screening IgG responses to overlapping peptides spanning Env 120–204 and viral sequence analysis of infected individuals defined differences in vaccine response that were associated with the presence of DPB1*13 and could be responsible for the protection observed. Overall, the underlying genetic findings indicate that HLA class II modulated the quantity, quality, and efficacy of antibody responses in the RV144 trial.

Next-Generation Sequencing Reveals That HLA-DRB3, -DRB4, and -DRB5 May Be Associated With Islet Autoantibodies and Risk for Childhood Type 1 Diabetes.

The possible contribution of HLA-DRB3, -DRB4, and -DRB5 alleles to type 1 diabetes risk and to insulin autoantibody (IAA), GAD65 (GAD autoantibody [GADA]), IA-2 antigen (IA-2A), or ZnT8 against either of the three amino acid variants R, W, or Q at position 325 (ZnT8RA, ZnT8WA, and ZnT8QA, respectively) at clinical diagnosis is unclear. Next-generation sequencing (NGS) was used to determine all DRB alleles in consecutively diagnosed patients ages 1–18 years with islet autoantibody–positive type 1 diabetes (n = 970) and control subjects (n = 448). DRB3, DRB4, or DRB5 alleles were tested for an association with the risk of DRB1 for autoantibodies, type 1 diabetes, or both. The association between type 1 diabetes and DRB1*03:01:01 was affected by DRB3*01:01:02 and DRB3*02:02:01. These DRB3 alleles were associated positively with GADA but negatively with ZnT8WA, IA-2A, and IAA. The negative association between type 1 diabetes and DRB1*13:01:01 was affected by DRB3*01:01:02 to increase the risk and by DRB3*02:02:01 to maintain a negative association. DRB4*01:03:01 was strongly associated with type 1 diabetes (P = 10−36), yet its association was extensively affected by DRB1 alleles from protective (DRB1*04:03:01) to high (DRB1*04:01:01) risk, but its association with DRB1*04:05:01 decreased the risk. HLA-DRB3, -DRB4, and -DRB5 affect type 1 diabetes risk and islet autoantibodies. HLA typing with NGS should prove useful to select participants for prevention or intervention trials.

Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes

It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high‐risk subjects into longitudinal studies of effective prevention strategies.